1. Field of the Invention
This invention relates generally to the field of verification of object identity by image correlation methods, and relates more particularly to a method and apparatus for verification of personnel identity by correlation of fingerprint images.
2. Description of the Relevant Art
Fingerprint matching is a commonly used and well accepted biometric method of personnel identification. Each fingerprint has a distinctive pattern of ridges and valleys that makes the fingerprint unique. The overall ridge patterns of fingerprints can be classified according to their distinctive shapes into several classes of morphology, including loops, arches, and whorls. The individual ridges of fingerprints have distinctive orientations, spacings, terminations, and bifurcations. Fingerprint matching methods are based on the premise that the combination of these features in any one fingerprint is unique.
One use of the fingerprint matching technique is in access control, wherein personnel are permitted or denied access to a controlled area based on comparisons with a data base of fingerprints. The controlled area may be a physical area, in which case access is controlled by a physical barrier, or a virtual area such as a computer program or data base, in which case access is controlled by an electric barrier. The data base of fingerprints is constructed during an enrollment procedure that consists of recording in some form the fingerprints of those individuals who are to be permitted access. Once the data base has been constructed, an individual will be granted access by way of a verification procedure only if the fingerprint presented for verification matches the stored fingerprint data of a particular enrolled individual.
Since manual methods of fingerprint matching are cumbersome, an automated method of personnel verification for access control is desirable. In order to be useful, such an automated method must accurately verify enrolled personnel, and must also accurately reject non-enrolled personnel. Inaccuracies in the verification process have been broken down into two types; a type one error is a false rejection of an enrolled individual, while a type two error is a false verification of a non-enrolled individual. Ideally, both type one and type two errors should be minimized, however, depending upon the application, an increased rate of one type of error may be tolerated in order to minimize the rate of the other type of error. For example, if the automated method is used to control access to a vault containing highly sensitive documents, the false verification rate should be very close, if not equal, to zero in order to protect against unauthorized access, while the inconveniences associated with a relatively large false rejection rate can be tolerated. On the other hand, if the cost of a false rejection is high and the penalty of a false verification is low, then a relatively high false verification rate can be tolerated in order to minimize the false rejection rate.
One factor that influences the accuracy of automated methods of access control is the repeatability of the process of imaging the fingerprint to be enrolled or verified. As indicated above, the use of fingerprint matching in access control utilizes two distinct procedures, enrollment and verification. In a typical automated method of access control, both the enrollment procedure and the verification procedure involve forming an optical image of the fingerprint of the individual to be enrolled or verified. The process of imaging a fingerprint typically involves sensing light reflected from the fingerprint, wherein the ridges and valleys of the fingerprint reflect the light differently. Inaccuracies may result from the imaging process itself by distortions of the fingerprint image caused by the imaging apparatus, and may also result from inconsistencies in alignment of the finger with the imaging apparatus or in variations of the moisture level of the finger surface. Another factor that influences the accuracy of automated methods of fingerprint matching is that the finger itself may change in size due to physiological or temperature related causes.
In addition to accuracy, other factors that effect the usefulness of automated methods of fingerprint matching include the cost of the automated apparatus, the speed of the enrollment and verification procedures, and the resistance of the method to tampering and misuse. Cost and speed are directly influenced by the efficiency of the enrollment procedure in accurately characterizing fingerprints by manipulating and storing a minimal amount of data.